Default Scheduling

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The default OKD pod scheduler is responsible for determining placement of new pods onto nodes within the cluster. It reads data from the pod and tries to find a node that is a good fit based on configured policies. It is completely independent and exists as a standalone/pluggable solution. It does not modify the pod and just creates a binding for the pod that ties the pod to the particular node.

Generic Scheduler

The existing generic scheduler is the default platform-provided scheduler engine that selects a node to host the pod in a three-step operation:

The scheduler .
The scheduler prioritizes the filtered list of nodes.
The scheduler for the pod.

The available nodes are filtered based on the constraints or requirements specified. This is done by running each node through the list of filter functions called predicates.

This is achieved by passing each node through a series of that assign it a score between 0 - 10, with 0 indicating a bad fit and 10 indicating a good fit to host the pod. The scheduler configuration can also take in a simple weight (positive numeric value) for each priority function. The node score provided by each priority function is multiplied by the weight (default weight for most priorities is 1) and then combined by adding the scores for each node provided by all the priorities. This weight attribute can be used by administrators to give higher importance to some priorities.

Select the Best Fit Node

The nodes are sorted based on their scores and the node with the highest score is selected to host the pod. If multiple nodes have the same high score, then one of them is selected at random.

Scheduler Policy

The selection of the predicate and defines the policy for the scheduler.

The scheduler configuration file is a JSON file that specifies the predicates and priorities the scheduler will consider.

In the absence of the scheduler policy file, the default configuration file, /etc/origin/master/scheduler.json, gets applied.

Default scheduler configuration file

Modifying Scheduler Policy

The scheduler policy is defined in a file on the master, named /etc/origin/master/scheduler.json by default, unless overridden by the field in the .

Sample modified scheduler configuration file

kind: "Policy"
version: "v1"
"predicates": [
        {
            "name": "PodFitsResources"
        },
        {
            "name": "NoDiskConflict"
        },
        {
            "name": "MatchNodeSelector"
        },
        {
            "name": "HostName"
        },
        {
            "argument": {
                "serviceAffinity": {
                    "labels": [
                        "region"
                    ]
                }
            },
            "name": "Region"
        }
    ],
    "priorities": [
        {
            "name": "LeastRequestedPriority",
            "weight": 1
        },
        {
            "name": "BalancedResourceAllocation",
            "weight": 1
        },
        {
            "name": "ServiceSpreadingPriority",
            "weight": 1
        },
        {
            "argument": {
                "serviceAntiAffinity": {
                    "label": "zone"
                }
            },
            "name": "Zone",
            "weight": 2
        }
    ]

To modify the scheduler policy:

Edit the scheduler configuration file to configure the desired default predicates and priorities. You can create a custom configuration, or use and modify one of the .
Add any configurable predicates and you require.

Restart the OKD for the changes to take effect.

# master-restart api
# master-restart controllers

Predicates are rules that filter out unqualified nodes.

There are several predicates provided by default in OKD. Some of these predicates can be customized by providing certain parameters. Multiple predicates can be combined to provide additional filtering of nodes.

These predicates do not take any configuration parameters or inputs from the user. These are specified in the scheduler configuration using their exact name.

Default Predicates

The default scheduler policy includes the following predicates:

NoVolumeZoneConflict checks that the volumes a pod requests are available in the zone.

{"name" : "NoVolumeZoneConflict"}

MaxEBSVolumeCount checks the maximum number of volumes that can be attached to an AWS instance.

{"name" : "MaxEBSVolumeCount"}

MaxGCEPDVolumeCount checks the maximum number of Google Compute Engine (GCE) Persistent Disks (PD).

{"name" : "MaxGCEPDVolumeCount"}

MatchInterPodAffinity checks if the pod affinity/antiaffinity rules permit the pod.

{"name" : "MatchInterPodAffinity"}

NoDiskConflict checks if the volume requested by a pod is available.

{"name" : "NoDiskConflict"}

PodToleratesNodeTaints checks if a pod can tolerate the node taints.

{"name" : "PodToleratesNodeTaints"}

CheckNodeMemoryPressure checks if a pod can be scheduled on a node with a memory pressure condition.

{"name" : "CheckNodeMemoryPressure"}

Other Static Predicates

CheckNodeDiskPressure checks if a pod can be scheduled on a node with a disk pressure condition.

{"name" : "CheckNodeDiskPressure"}

CheckVolumeBinding evaluates if a pod can fit based on the volumes, it requests, for both bound and unbound PVCs. * For PVCs that are bound, the predicate checks that the corresponding PV’s node affinity is satisfied by the given node. * For PVCs that are unbound, the predicate searched for available PVs that can satisfy the PVC requirements and that the PV node affinity is satisfied by the given node.

The predicate returns true if all bound PVCs have compatible PVs with the node, and if all unbound PVCs can be matched with an available and node-compatible PV.

{"name" : "CheckVolumeBinding"}

The CheckVolumeBinding predicate must be enabled in non-default schedulers.

CheckNodeCondition checks if a pod can be scheduled on a node reporting out of disk, network unavailable, or not ready conditions.

{"name" : "CheckNodeCondition"}

PodToleratesNodeNoExecuteTaints checks if a pod tolerations can tolerate a node NoExecute taints.

CheckNodeLabelPresence checks if all of the specified labels exist on a node, regardless of their value.

checkServiceAffinity checks that ServiceAffinity labels are homogeneous for pods that are scheduled on a node.

{"name" : "checkServiceAffinity"}

MaxAzureDiskVolumeCount checks the maximum number of Azure Disk Volumes.

{"name" : "MaxAzureDiskVolumeCount"}

General Predicates

The following general predicates check whether non-critical predicates and essential predicates pass. Non-critical predicates are the predicates that only non-critical pods need to pass and essential predicates are the predicates that all pods need to pass.

The default scheduler policy includes the general predicates.

Non-critical general predicates

PodFitsResources determines a fit based on resource availability (CPU, memory, GPU, and so forth). The nodes can declare their resource capacities and then pods can specify what resources they require. Fit is based on requested, rather than used resources.

{"name" : "PodFitsResources"}

Essential general predicates

PodFitsHostPorts determines if a node has free ports for the requested pod ports (absence of port conflicts).

{"name" : "PodFitsHostPorts"}

HostName determines fit based on the presence of the Host parameter and a string match with the name of the host.

{"name" : "HostName"}

MatchNodeSelector determines fit based on queries defined in the pod.

{"name" : "MatchNodeSelector"}

Configurable Predicates

You can configure these predicates in the scheduler configuration, by default /etc/origin/master/scheduler.json, to add labels to affect how the predicate functions.

Since these are configurable, multiple predicates of the same type (but different configuration parameters) can be combined as long as their user-defined names are different.

For information on using these priorities, see .

ServiceAffinity places pods on nodes based on the service running on that pod. Placing pods of the same service on the same or co-located nodes can lead to higher efficiency.

This predicate attempts to place pods with specific labels in its node selector on nodes that have the same label.

If the pod does not specify the labels in its node selector, then the first pod is placed on any node based on availability and all subsequent pods of the service are scheduled on nodes that have the same label values as that node.

"predicates":[
      {
         "name":"<name>", (1)
         "argument":{
            "serviceAffinity":{
               "labels":[
                  "<label>" (2)
               ]
            }
         }
      }
   ],

1	Specify a name for the predicate.
2	Specify a label to match.

For example:

        "name":"ZoneAffinity",
        "argument":{
            "serviceAffinity":{
                "labels":[
                    "rack"
                ]
            }
        }

For example. if the first pod of a service had a node selector rack was scheduled to a node with label , all the other subsequent pods belonging to the same service will be scheduled on nodes with the same region=rack label. For more information, see .

Multiple-level labels are also supported. Users can also specify all pods for a service to be scheduled on nodes within the same region and within the same zone (under the region).

The labelsPresence parameter checks whether a particular node has a specific label. The labels create node groups that the LabelPreference priority uses. Matching by label can be useful, for example, where nodes have their physical location or status defined by labels.

"predicates":[
      {
         "name":"<name>", (1)
         "argument":{
            "labelsPresence":{
               "labels":[
                  "<label>" (2)
                ],
                "presence": true (3)
            }
         }
      }
   ],

For example:

        "name":"RackPreferred",
        "argument":{
            "labelsPresence":{
                "labels":[
                    "rack",
                    "region"
                ],
                "presence": true
            }
        }

Available Priorities

Priorities are rules that rank remaining nodes according to preferences.

A custom set of priorities can be specified to configure the scheduler. There are several priorities provided by default in OKD. Other priorities can be customized by providing certain parameters. Multiple priorities can be combined and different weights can be given to each in order to impact the prioritization.

Static priorities do not take any configuration parameters from the user, except weight. A weight is required to be specified and cannot be 0 or negative.

Default Priorities

The default scheduler policy includes the following priorities. Each of the priority function has a weight of 1 except **NodePreferAvoidPodsPriority**, which has a weight of 10000.

SelectorSpreadPriority looks for services, replication controllers (RC), replication sets (RS), and stateful sets that match the pod, then finds existing pods that match those selectors. The scheduler favors nodes that have fewer existing matching pods. Then, it schedules the pod on a node with the smallest number of pods that match those selectors as the pod being scheduled.

{"name" : "SelectorSpreadPriority", "weight" : 1}

InterPodAffinityPriority computes a sum by iterating through the elements of weightedPodAffinityTerm and adding weight to the sum if the corresponding PodAffinityTerm is satisfied for that node. The node(s) with the highest sum are the most preferred.

{"name" : "InterPodAffinityPriority", "weight" : 1}

LeastRequestedPriority favors nodes with fewer requested resources. It calculates the percentage of memory and CPU requested by pods scheduled on the node, and prioritizes nodes that have the highest available/remaining capacity.

{"name" : "LeastRequestedPriority", "weight" : 1}

BalancedResourceAllocation favors nodes with balanced resource usage rate. It calculates the difference between the consumed CPU and memory as a fraction of capacity, and prioritizes the nodes based on how close the two metrics are to each other. This should always be used together with LeastRequestedPriority.

NodePreferAvoidPodsPriority ignores pods that are owned by a controller other than a replication controller.

{"name" : "NodePreferAvoidPodsPriority", "weight" : 10000}

NodeAffinityPriority prioritizes nodes according to node affinity scheduling preferences

{"name" : "NodeAffinityPriority", "weight" : 1}

TaintTolerationPriority prioritizes nodes that have a fewer number of intolerable taints on them for a pod. An intolerable taint is one which has key PreferNoSchedule.

{"name" : "TaintTolerationPriority", "weight" : 1}

Other Static Priorities

OKD also supports the following priorities:

EqualPriority gives an equal weight of 1 to all nodes, if no priority configurations are provided. We recommend using this priority only for testing environments.

{"name" : "EqualPriority", "weight" : 1}

MostRequestedPriority prioritizes nodes with most requested resources. It calculates the percentage of memory and CPU requested by pods scheduled on the node, and prioritizes based on the maximum of the average of the fraction of requested to capacity.

{"name" : "MostRequestedPriority", "weight" : 1}

ImageLocalityPriority prioritizes nodes that already have requested pod container’s images.

{"name" : "ImageLocalityPriority", "weight" : 1}

ServiceSpreadingPriority spreads pods by minimizing the number of pods belonging to the same service onto the same machine.

{"name" : "ServiceSpreadingPriority", "weight" : 1}

Configurable Priorities

You can configure these priorities in the scheduler configuration, by default /etc/origin/master/scheduler.json, to add labels to affect how the priorities.

The type of the priority function is identified by the argument that they take. Since these are configurable, multiple priorities of the same type (but different configuration parameters) can be combined as long as their user-defined names are different.

For information on using these priorities, see Modifying Scheduler Policy.

ServiceAntiAffinity takes a label and ensures a good spread of the pods belonging to the same service across the group of nodes based on the label values. It gives the same score to all nodes that have the same value for the specified label. It gives a higher score to nodes within a group with the least concentration of pods.

"priorities":[
    {
        "name":"<name>", (1)
        "weight" : 1 (2)
        "argument":{
            "serviceAntiAffinity":{
                "label":[
                    "<label>" (3)
                ]
            }
        }
    }
]

1	Specify a name for the priority.
2	Specify a weight. Enter a non-zero positive value.
3	Specify a label to match.

For example:

        "name":"RackSpread", (1)
        "weight" : 1 (2)
        "argument":{
            "serviceAntiAffinity":{
                "label": "rack" (3)
            }
        }

In some situations using ServiceAntiAffinity based on custom labels does not spread pod as expected. See .

*The labelPreference parameter gives priority based on the specified label. If the label is present on a node, that node is given priority. If no label is specified, priority is given to nodes that do not have a label.

"priorities":[
    {
        "name":"<name>", (1)
        "weight" : 1, (2)
        "argument":{
            "labelPreference":{
                "label": "<label>", (3)
                "presence": true (4)
            }
        }
    }

One of the important use cases for scheduling within OKD is to support flexible affinity and anti-affinity policies.

Infrastructure Topological Levels

Administrators can define multiple topological levels for their infrastructure (nodes) by specifying (e.g., region=r1, zone=z1, rack=s1).

These label names have no particular meaning and administrators are free to name their infrastructure levels anything (eg, city/building/room). Also, administrators can define any number of levels for their infrastructure topology, with three levels usually being adequate (such as: regions → zones → racks). Administrators can specify affinity and anti-affinity rules at each of these levels in any combination.

Administrators should be able to configure the scheduler to specify affinity at any topological level, or even at multiple levels. Affinity at a particular level indicates that all pods that belong to the same service are scheduled onto nodes that belong to the same level. This handles any latency requirements of applications by allowing administrators to ensure that peer pods do not end up being too geographically separated. If no node is available within the same affinity group to host the pod, then the pod is not scheduled.

If you need greater control over where the pods are scheduled, see Using Node Affinity and . These advanced scheduling features allow administrators to specify which node a pod can be scheduled on and to force or reject scheduling relative to other pods.

Anti Affinity

Administrators should be able to configure the scheduler to specify anti-affinity at any topological level, or even at multiple levels. Anti-affinity (or ‘spread’) at a particular level indicates that all pods that belong to the same service are spread across nodes that belong to that level. This ensures that the application is well spread for high availability purposes. The scheduler tries to balance the service pods across all applicable nodes as evenly as possible.

If you need greater control over where the pods are scheduled, see and Using Pod Affinity and Anti-affinity. These advanced scheduling features allow administrators to specify which node a pod can be scheduled on and to force or reject scheduling relative to other pods.

Sample Policy Configurations

The configuration below specifies the default scheduler configuration, if it were to be specified via the scheduler policy file.

kind: "Policy"
predicates:
...
  - name: "RegionZoneAffinity" (1)
    argument:
      serviceAffinity: (2)
        labels: (3)
          - "region"
          - "zone"
priorities:
...
  - name: "RackSpread" (4)
    weight: 1
    argument:
      serviceAntiAffinity: (5)
        label: "rack" (6)

1	The name for the predicate.
2	The type of predicate.
3	The labels for the predicate.
4	The name for the priority.
5	The .
6	The labels for the priority.

In all of the sample configurations below, the list of predicates and priority functions is truncated to include only the ones that pertain to the use case specified. In practice, a complete/meaningful scheduler policy should include most, if not all, of the default predicates and priorities listed above.

The following example defines three topological levels, region (affinity) → zone (affinity) → rack (anti-affinity):

kind: "Policy"
version: "v1"
predicates:
...
  - name: "RegionZoneAffinity"
    argument:
      serviceAffinity:
        labels:
          - "region"
          - "zone"
priorities:
...
  - name: "RackSpread"
    weight: 1
    argument:
      serviceAntiAffinity:
        label: "rack"

The following example defines three topological levels, city (affinity) → building (anti-affinity) → room (anti-affinity):

kind: "Policy"
version: "v1"
predicates:
...
  - name: "CityAffinity"
    argument:
      serviceAffinity:
        labels:
          - "city"
priorities:
...
  - name: "BuildingSpread"
    weight: 1
    argument:
      serviceAntiAffinity:
        label: "building"
  - name: "RoomSpread"
    weight: 1
    argument:
      serviceAntiAffinity:
        label: "room"

The following example combines both static and configurable predicates and also priorities:

kind: "Policy"
version: "v1"
predicates:
...
  - name: "RegionAffinity"
    argument:
      serviceAffinity:
        labels:
          - "region"
  - name: "RequireRegion"
    argument:
      labelsPresence:
        labels:
          - "region"
        presence: true
  - name: "BuildingNodesAvoid"
    argument:
      labelsPresence:
        labels:
          - "building"
        presence: false
  - name: "PodFitsPorts"
  - name: "MatchNodeSelector"
priorities:
...
  - name: "ZoneSpread"
    weight: 2
    argument:
      serviceAntiAffinity:
        label: "zone"
  - name: "ZonePreferred"
    weight: 1
    argument:
      labelPreference:
        label: "zone"
        presence: true
  - name: "ServiceSpreadingPriority"